The practical need for an effective student-centric organisation of active study by Bachelor’s and Master’s students of technical specialties at universities of the course on the fundamentals of optimal control theory determines the relevance of the author’s methodological approach presented in this paper. The approach is associated with the development of a comprehensive individual student assignment on computational multi-criteria nonlinear optimisation modelling of various optimal controls of linear one-dimensional motion of a controlled material point within the framework of the computational visualisation of the sequential nonlinear influence of the algebraic construct of each of the minimized functionals (A1)-(A20). They were mathematically constructed from systems engineering considerations on the completely non-obvious nonlinear dynamic features of each corresponding geometric profile of the desired optimal control signal. Most of the nonlinear formulas for the minimized functionals (A3)-(A20) proposed by the author of this study are original and principally new applied scientific results for the multidisciplinary field of engineering teaching of optimal control. The calculated results of nonlinear optimisation modelling presented in this study were obtained using the computing capabilities of JModelica-{1.17; 2.14} with the Optimica extension. The study can find wide engineering and pedagogical application in teaching university disciplines in automation, cybernetic, mechanical, electromechanical, information technology and computational optimisation cycles.
The problem of effective student learning of a new course within the framework of rational student goal setting is an “eternal” applied problem for the social and technical sciences. Each rational goal setting of the student was formulated in the form of a non-obvious mathematical construct of a nonlinear objective function that determined the minimized functional for the corresponding optimal control problem. Within the framework of the author’s approach to nonlinear modelling of various optimal goal-settings in student study of a new course, 35 optimal control problems for 35 pedagogically-admissible algebraic constructs for minimized functionals were mathematically posed, Optimica-formulated and numerically solved in JModelica-{1.17; 2.14}. As part of further generalization and psychological and pedagogical interpretation of the obtained graphical results of the numerical modelling, the following six strategies for studying a new course by a student were formulated: “Lazy Student” (Strategy A); “Procrastinator” (Strategy B); “Growing Student” (Strategy C); “Steady Student” (Strategy D); “Midterm Hero” or “Halfway Hero” (Strategy E), and “Starting Hero” or “Sprinting Hero” (Strategy F). The six strategies mentioned above for student learning of a new course seem to be a fairly concise summary of the individual educational efforts of both a school student, a university student, and a working professional.
The finite 1-bullet progressive silent duel is considered, in which each of the two duellists shoots with exponentially-concave reward. The duel models a system of one-decision-making competition between two identical intelligent competitors (duellists) through a quantized time span, in which the duellist benefits from shooting as late as possible but only by acting first. The duel is silenced because the duellist does not learn about the action of the other duellist until the very end moment of the duel. Thus, the duel is a symmetric matrix game whose optimal value is 0, and the set of optimal strategies is the same for both duellists, regardless of the duel size and how time is quantized. The duel time quantization is such that time progresses by the geometrical progression pattern, according to which every following time moment is the partial sum of the respective geometric series. In this duel, the duellist has the invariant unique optimal time moment, which is the duel middle, regardless of the number of time moments. Usually, the system manager benefits namely from such a solution, by which the manager latently forces both competitors to act at the invariant optimal moment, maintaining the system more stable and controllable.
Electromagnetic Launcher (EML) systems are classified into two main categories based on their fundamental operating principles: rail guns and coil guns. Rail guns accelerate a conductive projectile using magnetic force by passing a high current between two parallel rails, but they suffer from wear and heat accumulation due to mechanical contact. Coil launchers use electromagnets to accelerate ferromagnetic or conductive projectiles without contact, thus minimising energy losses and wear. Rail guns are preferred in military applications requiring high velocity and kinetic energy, whereas coil guns are more prominent in controlled acceleration applications such as space launch systems and laboratory experiments. Since the velocity of the generated electromagnetic field in coil launchers has no theoretical limit, the accelerated projectile also does not have a predefined velocity limit. However, the use of randomly sized coils and an increased number of sequential coils in coil guns disrupts the linearity of the projectile velocity increase. To address this issue, this study develops a “New Helical Coil Gun”, consisting of four-stage helical coils designed to achieve linear velocity increase. First, the self-inductance coefficient of a coil was simulated based on the time-dependent variations of the current passing through it, and the inductance value that could provide a maximum instantaneous current of 25A (without direction change) under laboratory conditions was determined. Then, the design of the helical coil with a rectangular cross-section to provide this coefficient value was implemented. This design was then transferred to the ANSYS Maxwell magnetic analysis software, where an optimisation process was conducted to determine the ideal projectile size that would maximise the magnetic force exerted on a ferromagnetic projectile when a 25 A current was applied to the coil. Following this stage, a “Helical Coil Gun”, composed of four-stage helical coils, was designed and manufactured based on the determined projectile and coil dimensions. Optical sensors were placed at the initial positions of the coils to measure the projectile’s velocity. An FPGA-based project was developed for data acquisition, processing, and triggering control. This project, designed using the LabVIEW FPGA module, was carried out on the NI myRIO-1950 board containing Xilinx FPGA. After each launch, the collected data was stored on a flash drive connected to myRIO and monitored in real time via a display. What distinguishes this study from literature is its approach to determining the optimal coil geometry by correlating the current variation characteristics with the coil’s self-inductance coefficient and using Genetic Algorithm-based optimisation to identify the ideal projectile size that achieves maximum velocity under maximum force. Experiments with the developed coil gun showed that the projectile velocity change from the beginning of the first coil to the end of the fourth coil was linear.
In fifth generation (5G) wireless networks, radio access techniques and multi-carrier waveforms play a vital role in meeting the diversified demands of ultra-low latency, massive connectivity, and higher throughput. Multi-access schemes used conventionally in 4G system was Orthogonal Multiple Access (OMA) technique. The OMA techniques suffer from inefficient spectrum utilization, high latency, and supports a limited number of users. Next-generation networks, Non-Orthogonal Multiple Access (NOMA), has a great potential, in which multiple users are simultaneously served using the same time, frequency, or code resource increasing the throughput. Code domain-NOMA (CD-NOMA) is the key technique implemented in the system design where multiple users are distinguished based on unique user-specific spreading codes. The NOMA system could significantly benefit from Universal Filtered Multi-Carrier (UFMC) modulation waveform in terms of flexibility, spectral efficiency, compatibility with Multiple Input Multiple Output (MIMO) technique, and relaxed synchronization requirements. The novel integrated system proposed in the paper is CD-NOMA-UFMC with convolutional codes. The major outcome of the paper is that the combination of UFMC air interface modulation technique with CD-NOMA access method can be the most effective way to meet the growing demands of 5G.
An approach to optimize centroid-based clustering of flat objects is suggested, which is practically important for efficiently solving metric facility location problems. In such problems, the task is to find the best warehouse locations to optimally service a given set of consumers. An example is assigning mobiles to base stations of a wireless communication network. We suggest a hexagonal-pattern-based approach to partition flat nodes into clusters quicker than the k-means algorithm and its modifications do. First, a hexagonal cell lattice is applied to nodes to approximately determine centroids of the clusters. Then the centroids are used as initial centroids to start the k-means algorithm. The suggested method is efficient for centroid-based clustering of dense nearly-square point clouds of 0.1 million points and greater by using no fewer than 6 lattice cells along an axis. Compared to k-means, our method is at least 10 % faster and it is about 0.01 to 0.07 % more accurate in regular Euclidean distances. In squared Euclidean distances, the accuracy gain is 0.14 to 0.21 %. Applying a hexagonal cell lattice determines an upper bound of the clustering quality gap.
This article offers an overview of distributed generation (DG) in distribution systems (DS). The primary goal of this study is to assess the performance of DGs in DS. Due to the rise in electrical energy consumption, it is anticipated that DG sources would be essential to DS. Future power generating networks have a bright outlook on consideration of DG’s potential for utilising alternative energy sources. The quality of power systems is a crucial concern for energy providers and consumers. In order to decrease reliance on fossil fuels for the production of electricity, distributed generations are gaining importance in the energy supply networks in many countries. Distributed generators are small units that generate electricity close to customer sites. These DGs use renewable energy methods such as wind energy, solar energy and geothermal energy. The incorporation of DGs into a conventional power supply system evolves in a number of side effects, including an increase in the number of short circuits, higher power losses, a decrease in the quality of the energy produced, voltage transients, problems with voltage stability, coordination issues regarding voltage regulation and protection, the possibility that system protection will not function correctly, and the fact that there is less residual current input as a result of the DG bidirectional power flows. This review paper discusses the impacts of the penetration of DG into DS and provides various strategies to mitigate these effects.
This paper presents the idea of implementing various techniques related to sampled-data control for magnetic levitation systems. The control laws are designed to track time-varying signals and employ the feedback linearization technique based on the approximate discrete-time model. State feedback control is introduced with the gains adjusted via the pole placement method. A positional form proportional-integral-derivative (PID) control uses the trapezoidal summation for the integral term and the backward difference method for the derivative term. An input-output linearization feedback control is the most promising one, which incorporates the integrator in addition to the position error and velocity error. The integral action involves the manipulation of regulation error and reduces it with time to improve performance. Finally, controllers were tested in real time for practical demonstration along with a comparison for comprehensive analysis.
Electric cars have a lot of promise in future energy markets as a manageable load. A popular vehicle-to-grid control interface, which enables the aggregation of the charging mechanism for energy management in the distribution grid, is one of the most significant road blocks to realize this opportunity. Understanding the ecology of electric transportation and integrating it in local communities to alleviate the energy shortage at peak hours is very complicated. In this research paper, recent standardization initiatives aimed at overcoming obstacles such as the integration of electric cars into smart grids are discussed. A charge control scheme focused on vehicle-to-grid connectivity is implemented. It is observed that the rise of environmentally sustainable energy sources, such as photovoltaic (PV) and wind energy, is straining the power network and their infrequent power generation is causing problems in power system operation, regulation and planning. The introduction of electric vehicles (EVs) into the electricity grid has been proposed to overcome grid load variations. Finally, the article discusses the incorporation of renewable energy sources and latest potential solutions involving electric vehicles.
This research study focuses on developing and implementing an IoT-based distribution transformer monitoring and protection system. The traditional methods of transformer protection and monitoring have proven to be inefficient and time-consuming, leading to the need for a more modern and effective solution. In this study, a low-cost prototype system is proposed to handle and control the main functions and problems of the distribution transformer through the internet. The proposed system allows for easy monitoring and protection of the transformer, enabling electric companies to improve efficiency and reduce labour and tool costs. The system is validated using Proteus software to simulate and obtain results from the hardware. The system results are displayed in multiple ways, including LCD, system bar, and internet, making it easier for electric companies and consumers in developing countries like Pakistan to monitor and control distribution transformers efficiently. This research study aims to provide valuable insights into the effectiveness of IoT-based distribution transformer monitoring and protection systems and their potential benefits in enhancing transformer performance and efficiency.
Power factor plays an important role in electrical industries. Low power factor results in loss of power and poor handling capacity. This factor can be overcome by using capacitors in parallel to the load. Since capacitor draws a leading while inductor draws a lagging current, hence by adjusting capacitor banks parallel to the load, it will level the power factor in the line. Earlier, the process of power factor improvement was done through manual connection of capacitor bank. Later a power factor corrector named the automated power factor corrector (APFC) was proposed. It uses a switched capacitor circuit to improve power factor. In this research, the power factor value from the load is measured and it also includes the installation of APFC unit using a PI controller. The design of this auto-adjustable power factor correction scheme is to ensure that the grid power system always operates under the specified power factor. Actual work of APFC is that it selects the capacitor bank for power factor improvement. The capacitor bank block will choose automatically to further improve the power factor. This process goes on until the required power factor is obtained. Later on, this will automatically turn off the connection between the capacitor bank and the circuit. Furthermore, power saving with power factor after improvement is also discussed in the paper. Here APFC plays a key role in order to decrease the time taken to correct the power factor, which is ultimately beneficial to increase the efficiency of the motors and all inductive loads.
This study examines the development of a novel FPGA-based RMF stirrer system. The system has been designed as a 3-phase system, with each phase being fed by PWM voltage with a phase difference of 120°. In case the system is driven at a 100 % duty cycle, the force acting on the magnetic fish remains continuous and constant until the subsequent phase changes. In such a case, at speeds under 400 rpm, the speed of the magnetic fish fails to be synchronized with the phase change speed. The magnetic fish, therefore, rotates more than 120° and the force is observed to cause a braking effect. Both fluid logic control (FLC) and virtual model control (VMC) were utilised to enable the system to be driven at a different duty cycle. The energy efficiency of the system for fluids with different viscosities has been attempted to be thereby improved with a lower current and shorter excitation time. With FLC and VMC control, the energy consumed by the system is reduced and the efficiency is increased, and approximately 95 % energy gain is obtained for liquids with viscosity up to 1.03 Pa·s. It has been experimentally proven that a lower limit value of the duty cycle of the PWM signal applied to the drive circuit of the system depends on the viscosity of the mixed liquid and a lower limit value increases with increasing viscosity. It has also been found that controlling the system with FLC and VMC does not have a great effect on the energy gain.
The major shortcoming in the extraction of electrical energy occurs due to partial shading over a limited area of vast spread solar panels underpinning reduction of efficiency. A number of panels are interconnected in series and parallel to form a photovoltaic (PV) array for large power plants and a shadow over a single cell deteriorates overall performance. As a consequence, several peaks are added to the P-V curve causing hotspots in PV panels, degradation of the PV system, and collapse of tracking algorithms. In order to minimize such issues in PV panels, an effective optimization technique is developed by reconfiguring the panels which are capable of reaching the full global power point in a PV system under partial shading conditions. The study proposes particle swarm optimization (PSO) using PV characteristics of Quaid-e-Azam Solar Plant (QASP) in Punjab, Pakistan1. In PSO, electrical connections of PV modules are changed keeping their physical locations unaltered aiming to improve the performance of the PV system. After reconfiguration, the algorithm finds the best combination of PV modules by equalizing the row currents followed by the comparison of row current, voltages, and power of panels. The proposed PSO is proved to be an efficient method for reconfiguring PV modules in very less computational time by increasing the output power of shaded modules.
The paper is dedicated to the development of hardware and software components for the autonomous water quality monitoring system (WQMS) for fishing farms. The system can measure main water quality parameters, storing and processing data on the remote server. The LoRaWAN technological solutions and infrastructure are utilized, providing the optimal tradeoff between data transmission range and adaptive power consumption. The main implementation and exploitation issues are described, and the proposed solutions are provided.
The Quantum Key Distribution (QKD) is a well-researched secure communication method for exchanging cryptographic keys only known by the shared participants. The vulnerable problem of a secret key distribution is the negotiation and the transfer over an insecure or untrusted channel. Novel further developments of the QKD communication method are part of in-field technologies and applications in communication devices, such as satellites. However, expensive physical test setups are necessary to improve new application possibilities of cryptographic protocol involving components of quantum mechanics and quantum laws of physics. Therefore, optical simulation software can play a part in essential QKD simulating and further developing quantum-based cryptosystems. In the paper, the authors consider a feasible QKD setup based on the BB84 protocol to create a symmetric key material based on achieving a linear key rate via optical simulation software. The paper still provides two experimental architecture designs to use the QKD for a cryptosystem.
The paper introduces a compact, thin flexible textile antenna integrated with an Electromagnetic Bandgap (EBG) and Defected Ground Structure (DGS) covering the Wireless Local Area Networks (WLAN) bands (2.4-2.485 GHz and 5.1-5.9 GHz) for emergency services and responses. The geometry and configuration of the proposed antenna are made from common clothing jeans fabric, which makes the antenna more flexible, thin, and conformal. A new configuration of EBG structure is developed using Minkowski fractal geometry as base geometry and a DGS with the complementary dumbbell-shaped slot to operate in WLAN standards. The EBG structure is used to isolate the antenna from the human body, whereas the DGS is used to improve the bandwidth and polarization purity. The prototype covers the WLAN bands with gains of 3.37 dBi and 6.47 dBi, a bandwidth of 115.9 MHz, and 398.06 MHz for the specified wireless bands. The integrated antenna demonstrates a Front to Back Ratio (FBR) of 16.77 dB and 32.72 dB, the radiation efficiency of 36.9 % and 73.8 %, and a better cross-polarization level at 2.45 GHz, 5.85 GHz, respectively. The antenna shows a high gain and an efficiency of about 70 % under the various bending scenario. Thus, the anticipated antenna is the most appropriate and potential candidate for wearable applications in various domains.
For the past decade, the main problem that has attracted researchers’ attention in aerial robotics is the position estimation or Simultaneous Localization and Mapping (SLAM) of Unmanned Aerial Vehicles (UAVs) where the GPS signal is poor or denied. This article reviews the strengths and weaknesses of existing methods in the field of aerial robotics. There are many different techniques and algorithms that are used to overcome the localization and mapping problem of these UAVs. These techniques and algorithms use different sensors, such as Red Green Blue-Depth (RGB_D), Light Detecting and Ranging (LIDAR), and Ultra-wideband (UWB). The most common technique is used, i.e., probability-based SLAM, which uses two algorithms: Linear Kalman Filter (LKF) and Extended Kalman Filter (EKF). LKF consists of five phases and this algorithm is just used for linear system problems. However, the EKF algorithm is used for non-linear systems. Aerial robots are used to perform many tasks, such as rescue, transportation, search, control, monitoring, and different military operations because of their vast top view. These properties are increasing their demand as compared to human service. In this paper, different techniques for the localization of aerial vehicles are discussed in terms of advantages and disadvantages, practicality and efficiency. This paper enables future researchers to find the suitable SLAM solution based on their problems; either the researcher is dealing with a linear problem or a non-linear problem.
The telecommunication and radioelectronic systems with redundancy are widely used in different branches of human activity. To provide the necessary reliability level of equipment, the operation system is utilized. That system contains intended use, maintenance, repair, technical condition monitoring, and others. The damages, faults and failures are usually observed during the lifecycle of telecommunication and radioelectronic systems. They can lead to deterioration of equipment technical condition. The deterioration of technical condition can be detected during observation of diagnostic variable and reliability parameter. This article concentrates on the synthesis and analysis of statistical data processing procedure for deterioration detection while operating telecommunication and radioelectronic systems with redundancy. For the purpose of reliability estimation based on different redundancy methods, statistical data processing procedure synthesis was carried out using multiple hypothesis testing and detection criterion. The analysis problem was solved using Monte- Carlo simulation method, which allowed constructing operating characteristics. The obtained results can be used in the process of design and improvement of operation systems for telecommunication and radioelectronic equipment.
The main aim of the article is to demonstrate the effectiveness of the use of ground penetrating radars to assess various objects using the example of assessing the current state of highways. The article uses the software developed by the authors and the corresponding mathematical models. The analysis of the results obtained is based on mathematical models that have proven their effectiveness and is time-tested. It should be emphasised that the main problem in assessing roads with non-rigid pavement is associated with a change in the main parameters of the layers – thickness and dielectric constant. Previously, we proposed a scheme for the layer-by-layer determination of the values of the relative permittivity and then - the subsequent determination of the thickness of each layer, starting from the top layer and ending with the base. The paper presents the results of experiments actually carried out by the authors with various GPRs, which not only have different values of the central frequency, but also have significant design differences. In addition, the results of processing real data using the software developed by the authors are presented. As a result, an improved method of signal calibration has been proposed, which makes it possible to increase the reliability of assessing the thickness of road surfaces, as well as other objects.
Abstract The issues of automatic vessel control in a storm are considered in the paper. Vessel control in a storm is the most difficult stage in the vessel’s wiring, as it requires quick decisions to be made in difficult conditions. Practical experience shows that the deterioration of the working conditions of the crew is usually associated with an increase in the number of control errors, which is completely unacceptable in stormy conditions. To assess the safe speed and course in a storm, Yu. V. Remez has proposed a universal storm diagram, which allows identifying unfavourable combinations of vessel speed and course angles of the waves – the resonant zones, and avoid them. The universal Remez diagram provides for graphical calculations, which, in combination with the visual determination of the wave parameters, gives a very low accuracy. The article examines the possibility of automatic control of a vessel in a storm by automatic measurement of motion parameters and wave parameters, automatic calculation in the onboard controller of the vessel optimal safe speed and course during a storm, automatic maintenance of the optimal safe speed and course of the vessel. The automatic control significantly increases the accuracy of calculations, excludes the human factor, reduces the depletion of the crew, and increases the reliability of the vessel control in a storm. The efficiency and effectiveness of the method, algorithmic and software were tested on Imitation Modelling Stand in a closed loop with mathematical vessel models of the navigation simulator Navi Trainer 5000.
